TNF-α inhibitor treatment and the risk of cardiovascular events in patients newly diagnosed with rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease that is mainly treated with various non-biologic and biologic disease modifying anti-rheumatic drugs (DMARDs). RA patients experience cardiovascular diseases (CVD) at a higher rate compared to the general population. Biologic DMARDs that inhibit the effects of the pro-inflammatory cytokine, tumor necrosis factor (TNF)-α which is implicated in various atherosclerotic processes, may reduce the risk of CVD. Very little evidence exists evaluating the association between TNF-inhibitors (TNF-Is) and CVD in early RA patients. Using data from Truven's MarketScan claims database for the period of 2007-2010, we first examined the factors influencing treatment with biologics in RA patients in a retrospective cohort study. We observed that treatment initiation with biologics in RA patients is associated with patient age, RA severity, RA type, pre-index non-biologic DMARD and steroid use, health insurance type, and drug benefit generosity. Neither the presence of cardiovascular risk factors, hypertension, hyperlipidemia or diabetes nor the history of CVD, including acute myocardial infarction, chronic heart failure, stroke or other CVD, were found to be associated with the initiation of biologic treatments. We then evaluated the impact of treatment with TNF-Is on the risk of incident CVD events in patients newly diagnosed with RA using a nested case-control design with incidence density sampling. We observed that the risk of an incident CVD event was reduced by current treatment with TNF-Is and non-biologic DMARDs compared to no treatment with DMARDs. Further, we observed that this protective effect was found to be associated with the duration of TNF-I and non-biologic DMARD use in a linear manner. Finally, we examined the independent effects of infliximab, adalimumab and etanercept on the risk of CVD in the same cohort. We observed that treatment with adalimumab, but not with infliximab and etanercept, was found to be associated with a reduced risk of incident CVD events compared to no treatment with DMARDs. In conclusion, we observed that early TNF-I or non-biologic DMARD treatment may play a vital role in reducing the increased CVD burden in RA patients, potentially by producing favorable changes in traditional cardiovascular risk factors and RA risk factors.Doctor of Philosoph

The “Dry-Run” Analysis: A Method for Evaluating Risk Scores for Confounding Control

A propensity score (PS) model's ability to control confounding can be assessed by evaluating covariate balance across exposure groups after PS adjustment. The optimal strategy for evaluating a disease risk score (DRS) model's ability to control confounding is less clear. DRS models cannot be evaluated through balance checks within the full population, and they are usually assessed through prediction diagnostics and goodness-of-fit tests. A proposed alternative is the "dry-run" analysis, which divides the unexposed population into "pseudo-exposed" and "pseudo-unexposed" groups so that differences on observed covariates resemble differences between the actual exposed and unexposed populations. With no exposure effect separating the pseudo-exposed and pseudo-unexposed groups, a DRS model is evaluated by its ability to retrieve an unconfounded null estimate after adjustment in this pseudo-population. We used simulations and an empirical example to compare traditional DRS performance metrics with the dry-run validation. In simulations, the dry run often improved assessment of confounding control, compared with the C statistic and goodness-of-fit tests. In the empirical example, PS and DRS matching gave similar results and showed good performance in terms of covariate balance (PS matching) and controlling confounding in the dry-run analysis (DRS matching). The dry-run analysis may prove useful in evaluating confounding control through DRS models

Comparative Cardiovascular Risk of Abatacept and Tumor Necrosis Factor Inhibitors in Patients With Rheumatoid Arthritis With and Without Diabetes Mellitus: A Multidatabase Cohort Study

Background: We examined the cardiovascular risk of abatacept compared with tumor necrosis factor (TNF) inhibitors in patients with rheumatoid arthritis with and without diabetes mellitus (DM). Methods and Results: We conducted a cohort study of patients with rheumatoid arthritis who newly started abatacept or TNF inhibitors using claims data from Medicare and MarketScan. The primary outcome was a composite cardiovascular end point of myocardial infarction (MI), stroke/transient ischemic attack, and coronary revascularization. To account for >60 baseline characteristics, abatacept initiators were 1:1 propensity score (PS) matched to TNF initiators in each database. Cox proportional hazards models estimated hazard ratio (HR) and 95% confidence interval (CI) in the PS‐matched cohort per database. A fixed‐effects meta‐analysis pooled database‐specific HRs. We included a total of 13 039 PS‐matched pairs of abatacept and TNF inhibitor initiators (6103 pairs in Medicare and 6936 pairs in MarketScan). A total of 34.7% in Medicare and 19.8% in MarketScan had baseline DM. The HR (95% CI) for the primary outcome associated with abatacept use versus TNF inhibitor was 0.81 (0.66–0.99) in Medicare and 0.95 (0.74–1.23) in MarketScan, with a pooled HR of 0.86 (95% CI, 0.73–1.01; P=0.3 for heterogeneity). The risk of the primary outcome was lower in abatacept initiators versus TNF inhibitors in the DM subgroup, with a pooled HR of 0.74 (95% CI, 0.57–0.96; P=0.7 for heterogeneity), but not in the non‐DM subgroup, with a pooled HR of 0.94 (95% CI, 0.77–1.14; P=0.4 for heterogeneity). Conclusions: In this large population‐based cohort of patients with rheumatoid arthritis, abatacept use appeared to be associated with a modestly reduced cardiovascular risk when compared with TNF inhibitor use, particularly in patients with DM

Exposure to prescription opioid analgesics in utero and risk of neonatal abstinence syndrome: population based cohort study

Objective: To provide absolute and relative risk estimates of neonatal abstinence syndrome (NAS) based on duration and timing of prescription opioid use during pregnancy in the presence or absence of additional NAS risk factors of history of opioid misuse or dependence, misuse of other substances, non-opioid psychotropic drug use, and smoking. Design: Observational cohort study. Setting: Medicaid data from 46 US states. Participants: Pregnant women filling at least one prescription for an opioid analgesic at any time during pregnancy for whom opioid exposure characteristics including duration of therapy: short term (<30 days) or long term (≥30 days); timing of use: early use (only in the first two trimesters) or late use (extending into the third trimester); and cumulative dose (in morphine equivalent milligrams) were assessed. Main outcome measure Diagnosis of NAS in liveborn infants. Results: 1705 cases of NAS were identified among 290 605 pregnant women filling opioid prescriptions, corresponding to an absolute risk of 5.9 per 1000 deliveries (95% confidence interval 5.6 to 6.2). Long term opioid use during pregnancy resulted in higher absolute risk of NAS per 1000 deliveries in the presence of additional risk factors of known opioid misuse (220.2 (200.8 to 241.0)), alcohol or other drug misuse (30.8 (26.1 to 36.0)), exposure to other psychotropic medications (13.1 (10.6 to 16.1)), and smoking (6.6 (4.3 to 9.6)) than in the absence of any of these risk factors (4.2 (3.3 to 5.4)). The corresponding risk estimates for short term use were 192.0 (175.8 to 209.3), 7.0 (6.0 to 8.2), 2.0 (1.5 to 2.6), 1.5 (1.0 to 2.0), and 0.7 (0.6 to 0.8) per 1000 deliveries, respectively. In propensity score matched analyses, long term prescription opioid use compared with short term use and late use compared with early use in pregnancy demonstrated greater risk of NAS (risk ratios 2.05 (95% confidence interval 1.81 to 2.33) and 1.24 (1.12 to 1.38), respectively). Conclusions: Use of prescription opioids during pregnancy is associated with a low absolute risk of NAS in the absence of additional risk factors. Long term use compared with short term use and late use compared with early use of prescription opioids are associated with increased NAS risk independent of additional risk factors

City Know-How

Human health and planetary health are influenced by city lifestyles, city leadership, and city development. For both, worrying trends are leading to increasing concern and it is imperative that human health and environmental impacts become core foci in urban policy. Changing trajectory will require concerted action; the journal Cities & Health is dedicated to supporting the flow of knowledge, in all directions, to help make this happen. We wish to foster communication between researchers, practitioners, policy-makers, communities, and decision-makers in cities. This is the purpose of the City Know-how section of the journal. ‘Research for city practice’ disseminates lessons from research by explaining key messages for city leaders, communities, and the professions involved in city policy and practice. ‘City shorts’ provide glimpses of what is being attempted or achieved ‘on the ground’ and ’case studies’ are where you will find evaluations of interventions. Last, ‘Commentary and debate’ extends conversations we are having to develop and mobilize much needed new thinking. Join in these conversations. In order to strengthen the community of interest, we would like to include many and varied voices, including those from younger practitioners and researchers who are supporting health and health equity in everyday urban lives

The Analysis of Teaching of Medical Schools (AToMS) survey: an analysis of 47,258 timetabled teaching events in 25 UK medical schools relating to timing, duration, teaching formats, teaching content, and problem-based learning.

BACKGROUND: What subjects UK medical schools teach, what ways they teach subjects, and how much they teach those subjects is unclear. Whether teaching differences matter is a separate, important question. This study provides a detailed picture of timetabled undergraduate teaching activity at 25 UK medical schools, particularly in relation to problem-based learning (PBL). METHOD: The Analysis of Teaching of Medical Schools (AToMS) survey used detailed timetables provided by 25 schools with standard 5-year courses. Timetabled teaching events were coded in terms of course year, duration, teaching format, and teaching content. Ten schools used PBL. Teaching times from timetables were validated against two other studies that had assessed GP teaching and lecture, seminar, and tutorial times. RESULTS: A total of 47,258 timetabled teaching events in the academic year 2014/2015 were analysed, including SSCs (student-selected components) and elective studies. A typical UK medical student receives 3960 timetabled hours of teaching during their 5-year course. There was a clear difference between the initial 2 years which mostly contained basic medical science content and the later 3 years which mostly consisted of clinical teaching, although some clinical teaching occurs in the first 2 years. Medical schools differed in duration, format, and content of teaching. Two main factors underlay most of the variation between schools, Traditional vs PBL teaching and Structured vs Unstructured teaching. A curriculum map comparing medical schools was constructed using those factors. PBL schools differed on a number of measures, having more PBL teaching time, fewer lectures, more GP teaching, less surgery, less formal teaching of basic science, and more sessions with unspecified content. DISCUSSION: UK medical schools differ in both format and content of teaching. PBL and non-PBL schools clearly differ, albeit with substantial variation within groups, and overlap in the middle. The important question of whether differences in teaching matter in terms of outcomes is analysed in a companion study (MedDifs) which examines how teaching differences relate to university infrastructure, entry requirements, student perceptions, and outcomes in Foundation Programme and postgraduate training

Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise.

BACKGROUND: Medical schools differ, particularly in their teaching, but it is unclear whether such differences matter, although influential claims are often made. The Medical School Differences (MedDifs) study brings together a wide range of measures of UK medical schools, including postgraduate performance, fitness to practise issues, specialty choice, preparedness, satisfaction, teaching styles, entry criteria and institutional factors. METHOD: Aggregated data were collected for 50 measures across 29 UK medical schools. Data include institutional history (e.g. rate of production of hospital and GP specialists in the past), curricular influences (e.g. PBL schools, spend per student, staff-student ratio), selection measures (e.g. entry grades), teaching and assessment (e.g. traditional vs PBL, specialty teaching, self-regulated learning), student satisfaction, Foundation selection scores, Foundation satisfaction, postgraduate examination performance and fitness to practise (postgraduate progression, GMC sanctions). Six specialties (General Practice, Psychiatry, Anaesthetics, Obstetrics and Gynaecology, Internal Medicine, Surgery) were examined in more detail. RESULTS: Medical school differences are stable across time (median alpha = 0.835). The 50 measures were highly correlated, 395 (32.2%) of 1225 correlations being significant with p < 0.05, and 201 (16.4%) reached a Tukey-adjusted criterion of p < 0.0025. Problem-based learning (PBL) schools differ on many measures, including lower performance on postgraduate assessments. While these are in part explained by lower entry grades, a surprising finding is that schools such as PBL schools which reported greater student satisfaction with feedback also showed lower performance at postgraduate examinations. More medical school teaching of psychiatry, surgery and anaesthetics did not result in more specialist trainees. Schools that taught more general practice did have more graduates entering GP training, but those graduates performed less well in MRCGP examinations, the negative correlation resulting from numbers of GP trainees and exam outcomes being affected both by non-traditional teaching and by greater historical production of GPs. Postgraduate exam outcomes were also higher in schools with more self-regulated learning, but lower in larger medical schools. A path model for 29 measures found a complex causal nexus, most measures causing or being caused by other measures. Postgraduate exam performance was influenced by earlier attainment, at entry to Foundation and entry to medical school (the so-called academic backbone), and by self-regulated learning. Foundation measures of satisfaction, including preparedness, had no subsequent influence on outcomes. Fitness to practise issues were more frequent in schools producing more male graduates and more GPs. CONCLUSIONS: Medical schools differ in large numbers of ways that are causally interconnected. Differences between schools in postgraduate examination performance, training problems and GMC sanctions have important implications for the quality of patient care and patient safety

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries